{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Tipping Problem Example\n",
    "ref: https://pythonhosted.org/scikit-fuzzy/auto_examples/plot_tipping_problem.html\n",
    "\n",
    "## DISCLAIMER!\n",
    "Kalo males, langsung ke block paling bawah aja"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import skfuzzy as fuzz\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Generate universe variables\n",
    "#   * Quality and service on subjective ranges [0, 10]\n",
    "#   * Tip has a range of [0, 25] in units of percentage points\n",
    "x_qual = np.arange(0, 11, 1)\n",
    "x_serv = np.arange(0, 11, 1)\n",
    "x_tip  = np.arange(0, 26, 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Generate fuzzy membership functions\n",
    "qual_lo = fuzz.trimf(x_qual, [0, 0, 5])\n",
    "qual_md = fuzz.trimf(x_qual, [0, 5, 10])\n",
    "qual_hi = fuzz.trimf(x_qual, [5, 10, 10])\n",
    "serv_lo = fuzz.trimf(x_serv, [0, 0, 5])\n",
    "serv_md = fuzz.trimf(x_serv, [0, 5, 10])\n",
    "serv_hi = fuzz.trimf(x_serv, [5, 10, 10])\n",
    "tip_lo = fuzz.trimf(x_tip, [0, 0, 13])\n",
    "tip_md = fuzz.trimf(x_tip, [0, 13, 25])\n",
    "tip_hi = fuzz.trimf(x_tip, [13, 25, 25])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x648 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualize these universes and membership functions\n",
    "fig, (ax0, ax1, ax2) = plt.subplots(nrows=3, figsize=(8, 9))\n",
    "\n",
    "ax0.plot(x_qual, qual_lo, 'b', linewidth=1.5, label='Bad')\n",
    "ax0.plot(x_qual, qual_md, 'g', linewidth=1.5, label='Decent')\n",
    "ax0.plot(x_qual, qual_hi, 'r', linewidth=1.5, label='Great')\n",
    "ax0.set_title('Food quality')\n",
    "ax0.legend()\n",
    "\n",
    "ax1.plot(x_serv, serv_lo, 'b', linewidth=1.5, label='Poor')\n",
    "ax1.plot(x_serv, serv_md, 'g', linewidth=1.5, label='Acceptable')\n",
    "ax1.plot(x_serv, serv_hi, 'r', linewidth=1.5, label='Amazing')\n",
    "ax1.set_title('Service quality')\n",
    "ax1.legend()\n",
    "\n",
    "ax2.plot(x_tip, tip_lo, 'b', linewidth=1.5, label='Low')\n",
    "ax2.plot(x_tip, tip_md, 'g', linewidth=1.5, label='Medium')\n",
    "ax2.plot(x_tip, tip_hi, 'r', linewidth=1.5, label='High')\n",
    "ax2.set_title('Tip amount')\n",
    "ax2.legend()\n",
    "\n",
    "# Turn off top/right axes\n",
    "for ax in (ax0, ax1, ax2):\n",
    "    ax.spines['top'].set_visible(False)\n",
    "    ax.spines['right'].set_visible(False)\n",
    "    ax.get_xaxis().tick_bottom()\n",
    "    ax.get_yaxis().tick_left()\n",
    "\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "qual_level_lo = 0.0\n",
      "qual_level_md = 0.7\n",
      "qual_level_hi = 0.30000000000000004\n",
      "serv_level_lo = 0.0\n",
      "serv_level_md = 0.03999999999999987\n",
      "serv_level_hi = 0.9600000000000002\n"
     ]
    }
   ],
   "source": [
    "# We need the activation of our fuzzy membership functions at these values.\n",
    "# The exact values 6.5 and 9.8 do not exist on our universes...\n",
    "# This is what fuzz.interp_membership exists for!\n",
    "qual_level_lo = fuzz.interp_membership(x_qual, qual_lo, 6.5)\n",
    "qual_level_md = fuzz.interp_membership(x_qual, qual_md, 6.5)\n",
    "qual_level_hi = fuzz.interp_membership(x_qual, qual_hi, 6.5)\n",
    "print(\"qual_level_lo = {}\".format(qual_level_lo))\n",
    "print(\"qual_level_md = {}\".format(qual_level_md))\n",
    "print(\"qual_level_hi = {}\".format(qual_level_hi))\n",
    "\n",
    "serv_level_lo = fuzz.interp_membership(x_serv, serv_lo, 9.8)\n",
    "serv_level_md = fuzz.interp_membership(x_serv, serv_md, 9.8)\n",
    "serv_level_hi = fuzz.interp_membership(x_serv, serv_hi, 9.8)\n",
    "print(\"serv_level_lo = {}\".format(serv_level_lo))\n",
    "print(\"serv_level_md = {}\".format(serv_level_md))\n",
    "print(\"serv_level_hi = {}\".format(serv_level_hi))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "active_rule1 = 0.0\n",
      "tip_activation_lo = [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      " 0. 0.]\n",
      "tip_activation_md = [0.   0.04 0.04 0.04 0.04 0.04 0.04 0.04 0.04 0.04 0.04 0.04 0.04 0.04\n",
      " 0.04 0.04 0.04 0.04 0.04 0.04 0.04 0.04 0.04 0.04 0.04 0.  ]\n",
      "active_rule3 = 0.9600000000000002\n",
      "tip_activation_hi = [0.         0.         0.         0.         0.         0.\n",
      " 0.         0.         0.         0.         0.         0.\n",
      " 0.         0.         0.08333333 0.16666667 0.25       0.33333333\n",
      " 0.41666667 0.5        0.58333333 0.66666667 0.75       0.83333333\n",
      " 0.91666667 0.96      ]\n"
     ]
    }
   ],
   "source": [
    "# Now we take our rules and apply them. Rule 1 concerns bad food OR service.\n",
    "# The OR operator means we take the maximum of these two.\n",
    "active_rule1 = np.fmax(qual_level_lo, serv_level_lo)\n",
    "print(\"active_rule1 = {}\".format(active_rule1))\n",
    "\n",
    "# Now we apply this by clipping the top off the corresponding output\n",
    "# membership function with `np.fmin`\n",
    "tip_activation_lo = np.fmin(active_rule1, tip_lo)  # removed entirely to 0\n",
    "print(\"tip_activation_lo = {}\".format(tip_activation_lo))\n",
    "\n",
    "# For rule 2 we connect acceptable service to medium tipping\n",
    "tip_activation_md = np.fmin(serv_level_md, tip_md)\n",
    "print(\"tip_activation_md = {}\".format(tip_activation_md))\n",
    "\n",
    "# For rule 3 we connect high service OR high food with high tipping\n",
    "active_rule3 = np.fmax(qual_level_hi, serv_level_hi)\n",
    "print(\"active_rule3 = {}\".format(active_rule3))\n",
    "tip_activation_hi = np.fmin(active_rule3, tip_hi)\n",
    "print(\"tip_activation_hi = {}\".format(tip_activation_hi))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "tip0 = np.zeros_like(x_tip)\n",
    "\n",
    "# Visualize this\n",
    "fig, ax0 = plt.subplots(figsize=(8, 3))\n",
    "\n",
    "ax0.fill_between(x_tip, tip0, tip_activation_lo, facecolor='b', alpha=0.7)\n",
    "ax0.plot(x_tip, tip_lo, 'b', linewidth=0.5, linestyle='--', )\n",
    "ax0.fill_between(x_tip, tip0, tip_activation_md, facecolor='g', alpha=0.7)\n",
    "ax0.plot(x_tip, tip_md, 'g', linewidth=0.5, linestyle='--')\n",
    "ax0.fill_between(x_tip, tip0, tip_activation_hi, facecolor='r', alpha=0.7)\n",
    "ax0.plot(x_tip, tip_hi, 'r', linewidth=0.5, linestyle='--')\n",
    "ax0.set_title('Output membership activity')\n",
    "\n",
    "# Turn off top/right axes\n",
    "for ax in (ax0,):\n",
    "    ax.spines['top'].set_visible(False)\n",
    "    ax.spines['right'].set_visible(False)\n",
    "    ax.get_xaxis().tick_bottom()\n",
    "    ax.get_yaxis().tick_left()\n",
    "\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "aggregated = [0.         0.04       0.04       0.04       0.04       0.04\n",
      " 0.04       0.04       0.04       0.04       0.04       0.04\n",
      " 0.04       0.04       0.08333333 0.16666667 0.25       0.33333333\n",
      " 0.41666667 0.5        0.58333333 0.66666667 0.75       0.83333333\n",
      " 0.91666667 0.96      ]\n",
      "tip = 19.86871794871795\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Aggregate all three output membership functions together\n",
    "aggregated = np.fmax(tip_activation_lo,\n",
    "                     np.fmax(tip_activation_md, tip_activation_hi))\n",
    "print(\"aggregated = {}\".format(aggregated))\n",
    "\n",
    "# Calculate defuzzified result\n",
    "tip = fuzz.defuzz(x_tip, aggregated, 'centroid')\n",
    "print(\"tip = {}\".format(tip))\n",
    "tip_activation = fuzz.interp_membership(x_tip, aggregated, tip)  # for plot\n",
    "\n",
    "# Visualize this\n",
    "fig, ax0 = plt.subplots(figsize=(8, 3))\n",
    "\n",
    "ax0.plot(x_tip, tip_lo, 'b', linewidth=0.5, linestyle='--', )\n",
    "ax0.plot(x_tip, tip_md, 'g', linewidth=0.5, linestyle='--')\n",
    "ax0.plot(x_tip, tip_hi, 'r', linewidth=0.5, linestyle='--')\n",
    "ax0.fill_between(x_tip, tip0, aggregated, facecolor='Orange', alpha=0.7)\n",
    "ax0.plot([tip, tip], [0, tip_activation], 'k', linewidth=1.5, alpha=0.9)\n",
    "ax0.set_title('Aggregated membership and result (line)')\n",
    "\n",
    "# Turn off top/right axes\n",
    "for ax in (ax0,):\n",
    "    ax.spines['top'].set_visible(False)\n",
    "    ax.spines['right'].set_visible(False)\n",
    "    ax.get_xaxis().tick_bottom()\n",
    "    ax.get_yaxis().tick_left()\n",
    "\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Function to predict the tip\n",
    "Now, to make these triangles useful, we define the fuzzy relationship between input and output variables. For the purposes of our example, consider three simple rules:\n",
    "\n",
    "1. If the food is bad OR the service is poor, then the tip will be low\n",
    "2. If the service is acceptable, then the tip will be medium\n",
    "3. If the food is great OR the service is amazing, then the tip will be high."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "def predict_tip(food_quality_score, service_score):\n",
    "    quality_level_low = fuzz.interp_membership(x_qual, qual_lo, food_quality_score)\n",
    "    quality_level_mid = fuzz.interp_membership(x_qual, qual_md, food_quality_score)\n",
    "    quality_level_high = fuzz.interp_membership(x_qual, qual_hi, food_quality_score)\n",
    "\n",
    "    service_level_low = fuzz.interp_membership(x_serv, serv_lo, service_score)\n",
    "    service_level_mid = fuzz.interp_membership(x_serv, serv_md, service_score)\n",
    "    service_level_high = fuzz.interp_membership(x_serv, serv_hi, service_score)\n",
    "    \n",
    "    # Rule 1\n",
    "    active_rule_1 = np.fmax(quality_level_low, service_level_low)\n",
    "    tip_activation_low = np.fmin(active_rule_1, tip_lo)\n",
    "    \n",
    "    # Rule 2\n",
    "    tip_activation_mid = np.fmin(service_level_mid, tip_md)\n",
    "    \n",
    "    # Rule 3\n",
    "    active_rule_3 = np.fmax(quality_level_high, service_level_high)\n",
    "    tip_activation_high = np.fmin(active_rule_3, tip_hi)\n",
    "    \n",
    "    # Aggregate all three output membership functions together\n",
    "    agg = np.fmax(tip_activation_low, np.fmax(tip_activation_mid, tip_activation_high))\n",
    "    \n",
    "    result_tip = fuzz.defuzz(x_tip, agg, 'centroid')\n",
    "    return result_tip"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "12.368205128205124"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "predict_tip(1, 9)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "conda_kernel",
   "language": "python",
   "name": "conda_kernel"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.9"
  }
 },
 "nbformat": 4,
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}
